Ayden successfully defended his PhD in December 2016 and is busy writing up his chapters for publication - congratulations, Ayden!
Ayden is a Bloomsbury Colleges PhD student based predominantly at Birkbeck, University of London, where he is currently conducting research into the biological basis of autism spectrum disorder (ASD).
Having always had a keen interest in brain and behavior, Ayden initially studied BSc Neuroscience at the University of Edinburgh. Following successful completion of his degree was a period of employment in the software development industry, before making a return to higher education with the intention of indulging his dual interests in neuroscience and computer science by moving into the field of bioinformatics/computational biology.
After being awarded a Pass with Distinction in MSc Bioinformatics from King’s College London in 2012, Ayden was awarded a place in the Bloomsbury Colleges PhD Studentship programme, to work on an interdisciplinary, integrative genomics project under the supervision of Dr Meaburn at Birkbeck and Dr Frank Dudbridge at the London School of Hygiene and Tropical Medicine. The project aims to tease apart genetic and environmental contributions to autism by developing a strategy to integrate multiple, diverse genomics datasets from a sample of identical twins discordant for ASD.
Scholarships and awards
Bloomsbury Colleges PhD Studentship (2013-2016).
The Genetics Society COnference Grant (2014)
Analysis of Genetic Association Studies - MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London (2014).
Bioinformatics analysis for next generation sequencing data - Barcelona Summer School of Genomics and Bioinformatics, Universitat Pompeu Fabra/CNAG (2013).
MSc Bioinformatics, King’s College London (2012)
BSc Neuroscience, The University of Edinburgh (2007)
A.Saffari et al., Genome-wide gene expression analysis of identical twins discordant for autism spectrum disorder
Ayden Saffari, Mat Silver, Emma Meaburn, Frank Dudbridge (2016) Estimation of a significance threshold for Epigenome-wide Association Studies. Under review